Dynamic bandwidth allocation method of Ethernet passive optical network

ABSTRACT

A dynamic bandwidth allocation method of an Ethernet passive optical network, comprises a predictor and a rule of QoS-promoted dynamic bandwidth allocation (PQ-DBA); the predictor predicts a client behavior and numbers of various kinds of packets by using a pipeline scheduling predictor consisted of a pipelined recurrent neural network (PRNN), and a learning rule of the extended recursive least squares (ERLS); the present invention establishes a better QoS traffic management for the OLT-allocated ONU bandwidth and client packets sent by priority.

BACKGROUND OF THE INVENTION

1. Field of the invention

The present invention relates to a dynamic bandwidth allocation (DBA)method of an Ethernet passive optical network (EPON), and moreparticularly, to a DBA method which is based on a pipeline schedulingpredictor consisted of a pipelined recurrent neural network (PRNN) and alearning rule of the extended recursive least squares (ERLS) to predicta client behavior and numbers of various kinds of packets for newarriving packets of each optical network unit (ONU) in a cycle time toprovide a reference for a optical line terminal (OLT) in grantingbandwidth allocation, thereby increasing the transmission performancebetween the OLT and the ONU while reducing a packet loss rate of theONU.

2. Description of the Prior Art

There have been studies of the scheduling of uplink signals in anEthernet passive optical network (EPON). Since the uplink bandwidth ofEPON is shared between ONUs, it is vital to allocate the uplinkbandwidth for ONUs. The earliest proposition for uplink signalsscheduling is Time Division Multiple Access (TDMA), as recited inreference [1], wherein each ONU is allocated a fixed timeslot. AlthoughTDMA is easy to implement in EPON, it can't handle the varying datapacket demands of ONUs and has a low bandwidth utilization rate.Therefore, Kramer (reference[2]) proposed a method of InterleavedPolling with Adaptive Cycle Time (IPACT) to deal with the burst trafficof data communication to improve the dynamic bandwidth allocation ofONU, this method is also proposed to the IEEE 802.3ah committee as astandard proposition for the MultiPoint Control Protocol (MPCP) of theEthernet passive optical network. However, the IPACT does not take theissues of delay and drop probability into consideration as to the QoSdemands of services provided by ONUs;

According to the rule of IPACT, packets from the ONU are processed in aFirst Come First Serve (FCFS) manner, so each packet would have a fixeddelay time, which is not acceptable for voice or real-time video trafficsince it could cause higher jitter. Many studies have been proposed toimprove QoS, such as the DBA-High Priority cited in reference [3], whichreduces the delay time and the jitter of high-priority services but alsoincreases the drop probability and the delay time of low-priorityservices and thus results in lower throughput for low-priority services.Furthermore, an intra-ONU, inter-ONU, two layer bandwidth allocation(TLBA) method has proposed to increase the cycle time of each ONU tosolve the unfairness in dealing with high- and low-priority services asrecited in reference [3]; however, it increases the delay time andreduces the throughput of high-priority services and fails to meet thedemands of burst traffic.

The burst-polling based delta DBA method (reference[6]) and the DBA withmultiple service (DBAM) method (reference[7]) are proposed to improvethe average delay time by predicting the arriving packets, however, themaximum window mechanism proposed in both references is designed to letthe OLT give more bandwidth than that required by the ONU and tends towaste valuable bandwidth and reduces transmission performance.

Therefore, the traditional DBA methods still present some shortcomingsto be overcome.

In view of the above-described deficiencies of the TDMA-based or theIPACT-based dynamic bandwidth allocation method, after years of constantefforts in research, the inventor of this invention has consequentlydeveloped and proposed a dynamic bandwidth allocation method of anEthernet passive optical network, which is based on a pipelinescheduling predictor consisted of a pipelined recurrent neural network(reference[8]) and a learning rule (reference[9]) of the extendedrecursive least squares (ERLS) in the present invention.

SUMMARY OF THE INVENTION

It is an object of the present invention to provide a dynamic bandwidthallocation method of an Ethernet passive optical network, wherein themethod predicts a client behavior and numbers of various kinds ofpackets by using a pipeline scheduling predictor consisted of apipelined recurrent neural network (PRNN), and a learning rule of theextended recursive least squares (ERLS), since the PRNN predictor isadvantageous in providing fast convergence and accurate prediction, itis suitable for making prediction of the Ethernet passive opticalnetwork, wherein each ONU uses a pig-tail mechanism for late-reportedtraffic type. Therefore, the predictor improves the bandwidthutilization rate of the Ethernet passive optical network.

It is another object of the present invention to provide a dynamicbandwidth allocation method of an Ethernet passive optical network,wherein the method proposes a rule of QoS-promoted Dynamic BandwidthAllocation (PQ-DBA) to improve the uplink/downlink algorithm of theInterleaved Polling with Adaptive Cycle Time (IPACT) for the Ethernetpassive optical network, as defined in IEEE 802.3ah, and to overcome thedeficiencies of other DBA methods in terms of QoS and client behaviorpredictions to maximize the bandwidth utilization. Besides, the PQ-DBAmethod can also improves the average data delay time and fairness forpriority-based packets.

In order to achieve the above objects, the dynamic bandwidth allocationmethod of an Ethernet passive optical network assumes that in anEthernet passive optical network (please refer to FIG. 1 for the systemstructure of the Ethernet passive optical network), the downlink rate isR_(E)(bps), the transmission rate between a client to each opticalnetwork unit (ONU) is R_(U) (bps); and an optical line terminal (OLT) isconnected to a 1:M splitter, which connects to M ONUs, numbered fromONU₁ to ONU_(M), the OLT broadcasts downlink packets to the ONUs foreach ONU to receive its own packet according to a Logic Link Identifier(LLID) and to drop packets not belonging to it. The OLT uses MultiPointControl Protocol (MPCP) to send a GRANT MPCPDU to the ONUs for each ONUto transmit its uplink data packets according to the given bandwidth andthe start/end time of optical signals defined by the GRANT MPCPDU.

Each ONU adds a REPORT MPCPDU in the last column of its uplink datapacket to inform the OLT and tells the OLT the number of unsent packetsin the ONU so as to request for the given bandwidth in the next GRANTMPCPDU.

The ONU_(i) receives three kinds of service packets (voice, video anddata) from the client and stores them in three queues (marked asQ_(0,i), Q_(1,i), Q_(2,i), 1≦i≦M) respectively, the values of packetsstored in the queue are recorded in L_(0,i), L_(1,i), L_(2,i), 1≦i≦M,respectively;

Besides, the present invention proposes three additional sets of QoSfactors:

(1) video packet delay threshold (T_(d)*)

(2) video packet drop probability threshold (P_(d)*); and

(3) data packet waiting time threshold (T_(w)*), all the factors arerecorded in the queue Q_(0,i), Q_(1,i), Q_(2,i), 1≦i≦M, also the numberof packets to be transmitted in the next cycle time will be calculatedand recorded in L_(dp,i), L_(d,i), L_(w,i), 1≦i≦M;

Furthermore, the OLT uses six packet values (L_(0,i), L_(dp,i), L_(d,i),L_(w,i), L_(1,i), L_(2,i)) of the REPORT MPCPDU sent by each ONU andcalculates with the reference value provided by the PRNN predictor, thenuses the PQ-DBA method to distribute an affordable number of packets toeach ONU_(i); a packet controller of the ONU relays the packets from theclients to corresponding queues and drops packets exceeding the queuestorage limit; however, in the present invention, the PQ-DBA method alsodetermines to drop a packet which is over the packet delay threshold(T_(d)*), that is, the packet is not transmitted within T_(d)* time.

A queue manager of the ONU controls the packet transmission between theOLT and the ONU(s) and is responsible for transmitting the REPORT MPCPDUmessages and a queue status of each ONU, the queue status of each ONU isto show and inform the OLT its remaining packet storage size for variousservices (measured in byte). Besides, using either TDMA and IPACT couldresult in the following scenario: when an ONU has sent out all itspackets at a certain point of time, the ONU responds to the OLT withREPORT MPCPDU=0, so for the next cycle time, the ONU gets no availablebandwidth (the OLT will set Grant=0 for the given bandwidth); later,assuming the ONU has new packets to send, but at this time there's noavailable bandwidth for the ONU (because queue packet value=0 in theprevious REPORT MPCPDU), the ONU must request bandwidth from the OLTonce again and waits for at least two or three cycle time to transmitclient's data packets.

It will take two to three cycle times for the OLT and the ONU uses GRANTand REPORT MPCPDU to communicate with each other, while during the cycletimes the client of the ONU could be still transmitting data. Therefore,the present invention uses the PRNN predictor to estimate transmissionrates of various kinds of packets of the ONU for each cycle time, and tomultiply the transmission rates with the cycle time to estimate a numberof new packets for each service (recorded in L_(0,i), L_(1,i), L_(2,i),L_(dp,i), L_(d,i), L_(w,i)) as a reference for the OLT in distributingthe bandwidth for each ONU, thereby improving the utilization rate ofthe Ethernet passive optical network.

Finally the OLT will sequentially estimates a new transmission rate anda number of new packets for each ONU_(i) in each cycle time, anddistributes a bandwidth for each ONU_(i) according to the PQ-DBA method.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a system structure of an Ethernet passive opticalnetwork using a dynamic bandwidth allocation method;

FIG. 2 illustrates a uplink/downlink communication view of an opticalline terminal and an optical network unit in the Ethernet passiveoptical network using the dynamic bandwidth allocation method;

FIG. 3 illustrates a structure of a pipelined recurrent neural networkpredictor of the Ethernet passive optical network using the dynamicbandwidth allocation method;

FIG. 4 illustrates a functional structure of recurrent neural networkmodules of the Ethernet passive optical network using the dynamicbandwidth allocation method; and

FIG. 5 illustrates a flowchart of a PQ-DBA method of the dynamicbandwidth allocation method used in the Ethernet passive opticalnetwork.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

Please refer to FIG. 1 for a system structure of an Ethernet passiveoptical network using a dynamic bandwidth allocation method, whichcomprises:

a optical line terminal (OLT) 1 coupling with a splitter 2 forbroadcasting downlink packets to a plurality of optical network units(ONU) 3, the OLT 1 further comprising a pipelined recurrent neuralnetwork (PRNN) 11 for distributing a GRANT MultiPoint Control ProtocolData Unit (MPCPDU);

the splitter 2 coupling with the OLT 1 and the plurality of ONUs 3,wherein the splitter 2 is a one-to-multiple-point splitter;

the plurality of ONUs 3 coupling with the splitter 2 and a plurality ofclients 4, each ONU receiving its own packets according to a Logic LinkIdentifier (LLD) and dropping packets not matching with its LLD; eachONU comprising a queue controller 31, a voice packet queue 321, a videopacket queue 322, a data packet queue 323 and a packet controller 33.Besides, the plurality of ONUs 3 would add a REPORT MPCPDU in the lastcolumn of its uplink data packet to inform the OLT 1 and tells the OLT 1the number of unsent packets in the ONU 3 so as to request for the givenbandwidth in the next GRANT MPCPDU;

the plurality of clients 4 coupling with the plurality of ONUs 3, sincethe OLT 1 and the plurality of ONUs 3 communicate with each other byusing GRANT and REPORT MPCPDUs, there could be a two-to-three-cycle-timedelay during which the plurality of clients 4 is still transmittingdata;

The OLT 1 in the present invention comprises a pipeline schedulingpredictor consisted of a pipelined recurrent neural network (PRNN) and arule of QoS-promoted dynamic bandwidth allocation (PQ-DBA) method,therefore it is suitable for handling signals having high complexity andrequiring short convergence time and nonlinear/non-stationaryprediction. When it is required to predict the new packet transmissionrate {tilde over (λ)}_(m,i)(n+1) of (N+1)th cycle time of the ONU_(i),then it can be obtained by using the previous p packet transmission rateof the ONU, namely λ_(m,i)(n), λ_(m,i)(n−1), . . . , λ_(m,i)(n−p+1) asthe reference input to calculate the estimate value of {tilde over(λ)}_(m,i)(n+1). Therefore, the present invention uses the PRNNpredictor to estimate transmission rates of various kinds of packets ofthe ONU 3 for each cycle time, and to multiply the transmission rateswith the cycle time to estimate a number of new packets for each service(recorded in L_(0,i), L_(1,i), L_(2,i), L_(dp,i), L_(d,i), L_(w,i)) as areference for the OLT 1 in distributing the bandwidth for each ONU 3,thereby improving the utilization rate of the Ethernet passive opticalnetwork.

Please refer to FIG. 2 for a uplink/downlink communication view of theOLT 1 and the ONU 3 in the Ethernet passive optical network using thedynamic bandwidth allocation method. The way the OLT and the ONUcommunicates is that, when the OLT 1 is at the (n−1)th cycle time(T_(i)(n−1)), starting from T1 in FIG. 2, the OLT 1 has received all thequeue information from the ONU_(i)(L_(m,i)(n−1), wherein m={0,1,2},1≦i≦M, and L_(dp,i)(n−1), L_(d,i)(n−1), and L_(w,i)(n−1)), and the OLT 1uses the PRNN predictor to estimate the number of new packets fromONU_(i) at T_(i)(n−1) time, as a reference for the PQ-DBA method indistributing a bandwidth (G_(m,i)(n)) for the ONU_(i); and the OLT 1calculates the number of new packets in Q_(m,i) of the ONU_(i) at the(n−1)th cycle time as:

-   1. High Loading: when L_(m,i)(n−1)>0, which means the predicted    value is smaller than the real number A_(m,i)(n−1) of incoming    packets, or the maximum given bandwidth is less than required    bandwidth from L_(m,i)(n−2) of ONU_(i), then the number of new    packets of queue Q_(m,i) in T_(i)(n−1) time would be:    {tilde over (E)} _(m,i)(n−1)=G _(m,i)(n−1)−L _(m,i)(n−2)+L    _(m,i)(n−1)˜A _(m,i)(n−1)=λ_(m,i)(n−1)*T _(i)(n−1)-   2. Low Loading: when L_(m,i)(n−1)=0, which means the predicted value    could be higher that the real number A_(m,i)(n−1) of incoming    packets, now the number of new packets is unknown, so it is chosen    to be the average of previous numbers of incoming packets:

${{\overset{\sim}{E}}_{m,i}\left( {n - 1} \right)} = {{\frac{{{\overset{\sim}{E}}_{m,i}\left( {n - 2} \right)} + {\sum\limits_{k = 3}^{n - 1}\;{A_{m,i}\left( {n - k} \right)}}}{n - 2} \sim {A_{m,i}\left( {n - 1} \right)}} = {{\lambda_{m,i}\left( {n - 1} \right)}*{T_{i}\left( {n - 1} \right)}}}$

Where λ_(m,i)(n−1)=A_(m,i)(n−1)/T_(i)(n−1).

-   3. The number of packets in the (n−1) cycle time is {tilde over    (E)}_(m,i)(n−1)={tilde over (λ)}_(m,i)(n−1)*T_(i)(n−1), from FIG. 2,    G_(m,i)(n)=[L_(m,i)(n−1)+{tilde over    (E)}_(m,i)(n−1)]≅[L_(m,i)(n−1)+A_(m,i)(n−1)].

In order to minimize L_(m,i)(n) (maximizing the bandwidth utilization),the bandwidth G_(m,i)(n) distributed by the OLT 1 not only should meetthe demands of L_(m,i)(n−1) packets in Q_(m,i), but also should meet thedemands of (A_(m,i)(n−1)) packets added in T_(i)(n−1) time; when theprediction is closer to reality, the L_(m,i)(n) is less, however, thevalue of L_(m,i)(n) is unknown at this time, we can only use theinformation obtained before the (n−1)th cycle time, such asλ_(m,i)(n−2), λ_(m,i)(n−3), λ_(m,i)(n−4) . . . to predict the new packettransmission rate {tilde over (λ)}_(m,i)(n−1) in the (n−1)th cycle timeT_(i)(n−1).

Please refer to FIG. 3 for a structure of the PRNN predictor of theEthernet passive optical network using the dynamic bandwidth allocationmethod. The structure of the PRNN predictor is based on a nonlinearautoregressive-moving average (NARMA) model, which comprises rhierarchies, each hierarchy comprises a recurrent neural network module(RNN) module and a comparator; wherein a first output (y_(1,1)(n)) ofthe first recurrent neural network module is the only output of the PRNNpredictor, while the first outputs of other recurrent neural networkmodules (y_(i,1)(n), 2≦i≦r) are all coupled with the recurrent neuralnetwork module of the next hierarchy, and the other N−1 outputs(y_(i,2)(n)˜y_(i,N)(n)) of each recurrent neural network module are allfed back to the original recurrent neural network module, and the output(y_(r,1)(n)) of the last recurrent neural network module is also fedback to the last recurrent neural network module.

Please refer to FIG. 4 for a functional structure of recurrent neuralnetwork modules of the Ethernet passive optical network using thedynamic bandwidth allocation method, wherein each recurrent neuralnetwork module comprises N neural cells (v₁˜v_(N)), p external inputports, N feedback input ports and one bias input port; the externalinput port receives new packet transmission rate λ_(p)(k), n−p+1≦k≦n,the N feedback input ports comprises N−1 self-feedback(y_(i,2)(n)˜y_(i,N)(n) in FIG. 4) outputs and theoutput(y_(r,1)(n)˜y_(2,1)(n) in FIG. 3) of the previous recurrent neuralnetwork module, the bias input value is set as 1. Since each recurrentneural network module is a sub-predictor of the r-hierarchy PRNNpredictor, the sub-predictor would have a error value, which is definedas e_(i)(n)=λ(n−i+1)−y_(i,1)(n), 1≦i≦r;

The error value is provided for updating a weight in each recurrentneural network module. The present invention uses an extended recursiveleast squares (ERLS) rule as the learning algorithm for the PRNNpredictor to update the weight w_(ij). Furthermore, in order to reducethe complexity of the predictor, all recurrent neural network module inthe present invention are equipped with the same weightedarray[W](synaptic weight matrix), so the sum E(n) of errors for eachsub-predictor must be obtained to adjust the weight, which is definedas:

${{E(n)} = {\sum\limits_{i = 1}^{r}\;{\alpha_{n}^{i - 1}*{\mathbb{e}}\;{i^{2}(n)}}}},{\alpha_{n} \in \left( {0,1} \right\rbrack},$and α_(n) is an exponential forgetting factor, which is between 0 and 1.Since the ERLS method uses the present and the previous (r−1) errors tomake prediction, in order to achieve better results, the predicted valueof new packet transmission rate {tilde over (λ)}_(m,i)(n) in T_(i)(n)time is used to estimate the number {tilde over (E)}_(m,i)(n) of newpackets in T_(i)(n) cycle time, which is {tilde over(E)}_(m,i)(n)={tilde over (λ)}_(m,i)(n)×T_(i)(n); however, the IPACTmethod cannot provide priority-based mechanism for the ONUs to meet theQoS demands, that is, the voice and video packets are more sensitive tonetwork delays, and the data packets could have starvation problems forlong waiting time.

Therefore, the present invention proposes a QoS-promoted DynamicBandwidth Allocation (PQ-DBA) method for maximizing the bandwidthutilization and for meeting QoS requirements, the method comprises:

The first is to determine priorities of client traffic types and qualityof service (QoS) parameters, in the PQ-DBA method, the client traffictypes are classified into six levels:

-   -   1) highest priority: a voice packet Q_(0,i);    -   2) second priority: a video packet L_(dp,i) facing a drop        probability;    -   3) third priority: a video packet L_(d,i) facing a delay        problem;    -   4) fourth priority: a data packet L_(w,i) facing a delay        problem;    -   5) fifth priority: a common video packet Q_(1,i); and    -   6) lowest priority: a common data packet Q_(2,i).

Since the voice service and the video service are both real-timeservices and sensitive to delays, therefore the resent inventiondiscloses three QoS to increase their traffic priorities:

-   -   1) video packet delay threshold (T_(d)*): recorded in L_(dp,i)        to represent the number of unsent video packets to be dropped in        the next cycle time (since the time delay of these packets are        way beyond the threshold value T_(d)* at the end of the next        cycle time);    -   2) video packet drop probability threshold (P_(d)*): the        tolerable video packet drop probability in maintaining video        service quality, which is recorded in L_(d,i) to represent the        number of video packets needed to be sent out in the next cycle        time for meeting the requirement of the drop probability P_(d)*        (because the time delay of these packets are way beyond the        threshold value T_(d)* at the end of the next cycle time, and a        ratio P_(d)* of packets will be randomly dropped); however, the        number of randomly dropped packets can't be too large to affect        the QoS of video service.    -   3) data packet waiting time threshold (T_(w)*): recorded in        L_(w,i) to represent the number of data packets exceeding the        waiting time threshold (T_(w)*) to avoid data packets exceeding        the waiting time threshold and entering a starvation mode or        even initiating a Random Early Drop (RED) mechanism.

The second step is to determine a bandwidth for each client traffictype, the PQ-DBA method will let the OLT 1 distribute all availablebandwidth to ONU_(i) from the highest priority to the lowest priorityuntil all available bandwidth is used.

Please refer to FIG. 5 for a flowchart of a PQ-DBA method of the dynamicbandwidth allocation method used in the Ethernet passive opticalnetwork, wherein the ONU 3 (ONU_(i), 1≦i≦M) transmits L_(0,I), L_(dp,I),L_(d,I), L_(w,I), L_(1,I), L_(2,i) and 1≦i≦M to the OLT 1, and the OLT 1receives the values of L_(0,I), L_(dp,I), L_(d,I), L_(w,I), L_(1,I),L_(2,i) in the REPORT MPCPDUs from the ONU_(i), calculates them with theprediction values from the PRNN predictor and then sends the GrantMPCPDUs specifying the distributed bandwidth G_(0,i), G_(1,i) andG_(2,i) to the ONUs 3 (ONU_(i), 1≦i≦M), assuming the total bandwidth ofeach ONU_(i) is B, the method comprises:

-   Step 1: distributing a voice bandwidth (G′_(0,i)) to the first    priority traffic type according to a packet value L_(0,i) stored in    a queue by the ONU_(i);-   Step 2: distributing a video bandwidth (G′_(1,i)) to the second and    third priority traffic types according to a remaining bandwidth

$B - {\sum\limits_{i = 1}^{M}\; G_{0,i}^{\prime}}$from step 1 and packet values L_(d,i) of the video packet facing a dropprobability and the packet values L_(dp,i) of the video packet facing adelay problem of the ONU_(i);

-   Step 3: distributing a data bandwidth (G′_(2,i)) to the fourth    priority traffic type according to a remaining bandwidth

$B - {\sum\limits_{i = 1}^{M}\;\left\lbrack {G_{0,i}^{\prime} + G_{1,i}^{\prime}} \right\rbrack}$from step 2 and a packet value L_(w,i) of the data packet of theONU_(i);

-   Step 4: distributing a common video bandwidth (G″_(1,i)) to the    fifth priority traffic type according to a remaining bandwidth

$B - {\sum\limits_{i = 1}^{M}\;\left\lbrack {G_{0,i}^{\prime} + G_{1,i}^{\prime} + G_{2,i}^{\prime}} \right\rbrack}$from step3 and a remaining packet value L_(1,i)-L_(d,i) of the commonvideo packet queue Q_(1,i) of the ONU_(i);

-   Step 5: distributing a data bandwidth (G″_(2,i)) to the lowest    priority traffic type according to a remaining bandwidth

$B - {\sum\limits_{i = 1}^{M}\;\left\lbrack {G_{0,i}^{\prime} + G_{1,i}^{\prime} + G_{2,i}^{\prime} + G_{1,i}^{\prime}} \right\rbrack}$from step4 and a remaining packet value L_(2,i)-L_(w,i) of the commondata packet queue Q_(2,i) of the ONU_(i);

-   Step 6: distributing remaining bandwidth, if there's still available    bandwidth after all required bandwidth is distributed to the ONUs,    that is

${{B - {\sum\limits_{i = 1}^{M}\;\left\lbrack {G_{0,i}^{\prime} + G_{1,i}^{\prime} + G_{2,i}^{\prime} + G_{1,i}^{''} + G_{2,i}^{''}} \right\rbrack}} > 0},$then the remaining bandwidth is again distributed to the voice bandwidth(G″_(0,i)) and video bandwidth (G′″_(1,i)) of the ONU_(i) according tothe ratio of packet values L_(0,i) and L_(1,i); and

-   Step 7: sending GRANT MPCPDU (voice), wherein the distributed    bandwidth G_(0,i)(voice), G_(1,i)(video), G_(2,i)(data) is the sum    of the respective distributed value of the previous six steps.

$\quad\left\{ \begin{matrix}{G_{0,i} = {G_{0,i}^{\prime} + {G_{2,i}^{''}.}}} \\{G_{1,i} = {G_{1,i}^{\prime} + G_{1,i}^{''} + {G_{1,i}^{\prime\prime\prime}.}}} \\{G_{2,i} = {G_{2,i}^{\prime} + {G_{2,i}^{''}.}}}\end{matrix} \right.$

The present invention discloses a dynamic bandwidth allocation method ofthe Ethernet passive optical network, while compared with prior arttechniques, is advantageous in:

-   -   1. The present invention can accurately predict traffic (arrived        packets) for each service in one cycle time and provides a        reference for the OLT to distribute bandwidth to each ONU.    -   2. The PRNN predictor is advantageous in providing fast        convergence and accurate prediction; therefore it is suitable        for making prediction of the Ethernet passive optical network,        wherein each ONU uses a pig-tail mechanism for late-reported        traffic type. Using the PRNN can obtain more accurate and        closer-to-reality client behaviors and numbers of various kinds        of packets to improve transmission performance between the OLT        and the ONU, even improves the bandwidth utilization rate of the        Ethernet passive optical network.    -   3. The present invention provides better QoS, because the PQ-DBA        method can establish better traffic assurance based on        priorities of packets of different traffic types, besides, the        PQ-DBA method designs additional QoS parameters to assure the        service quality of every service (including voice, video and        data).    -   4. The present invention can dynamically upgrade client's        traffic priority according to a video packet delay threshold        (T_(d)*), a video packet drop probability threshold (P_(d)*) and        a data packet waiting time threshold (T_(w)*) and by promoting a        low priority packet which must be sent out in the next cycle        time to avoid being dropped to become a higher priority packet,        so the packets of the same packet type from the ONU will be        transmitted in advance to improve service quality.    -   5. The PRNN/ERLS predictor disclosed in the preset invention        could solve the problem encountered by the TDMA and the IPACT        method since there could be a two-to-three cycle time delay for        data packets from the client (in the worst case).

Many changes and modifications in the above described embodiment of theinvention can, of course, be carried out without departing from thescope thereof. Accordingly, to promote the progress in science and theuseful arts, the invention is disclosed and is intended to be limitedonly by the scope of the appended claims.

REFERENCES

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1. A dynamic bandwidth allocation method of an Ethernet passive opticalnetwork (EPON), comprising: 1) predicting a client behavior and numbersof various kinds of packets by using a pipelined recurrent neuralnetwork and an extended recursive least squares (ERLS) rule; 2)maximizing a bandwidth utilization rate of the EPON by using aQoS-promoted Dynamic Bandwidth Allocation method; wherein the Ethernetpassive optical network comprises: a optical line terminal (OLT)coupling with a splitter for broadcasting downlink packets to aplurality of ONUs, the OLT further comprising a pipelined recurrentneural network (PRNN) for distributing a GRANT MultiPoint ControlProtocol Data Unit (MPCPDU); the splitter coupling with the OLT and theplurality of ONUs, wherein the splitter is a one-to-multiple-pointsplitter; the plurality of ONUs coupling with the splitter and aplurality of clients, each ONU receiving its own packets according to aLogic Link Identifier (LLD) and dropping packets not matching with itsLLD; the plurality of clients coupling with the plurality of ONUs, sincethe OLT and the plurality of ONUs communicate with each other by usingGRANT and REPORT MPCPDUs, there could be a two-to-three-cycle-time delayduring which the plurality of clients is still transmitting data.
 2. Thedynamic bandwidth allocation method of an Ethernet passive opticalnetwork as claimed in claim 1, wherein the ONU comprises a queuecontroller, a voice packet queue, a video packet queue, a data packetqueue and a packet controller.
 3. The dynamic bandwidth allocationmethod of an Ethernet passive optical network as claimed in claim 1,wherein the PRNN predictor comprises r hierarchies, each hierarchycomprises a recurrent neural network module and a comparator.
 4. Thedynamic bandwidth allocation method of an Ethernet passive opticalnetwork as claimed in claim 3, wherein a first output (y_(1,1)(n)) ofthe first recurrent neural network module is the only output of the PRNNpredictor, while the first outputs of other recurrent neural networkmodules (y_(i,1)(n), 2≦i≦r) are all coupled with the recurrent neuralnetwork module of the next hierarchy, and the other N−1 outputs(y_(i,2)(n)˜y_(i,N)(n)) of each recurrent neural network module are allfed back to the original recurrent neural network module, and the output(y_(r,1)(n)) of the last recurrent neural network module is also fedback to the last recurrent neural network module.
 5. The dynamicbandwidth allocation method of an Ethernet passive optical network asclaimed in claim 3, wherein the recurrent neural network modulecomprises N neural cells (v₁˜v_(N)), p external input ports, N feedbackinput ports and one bias input port.
 6. The dynamic bandwidth allocationmethod of an Ethernet passive optical network as claimed in claim 3,wherein the external input port receives new packet transmission rateλ_(p)(k), n−p+1≦k≦n the N feedback input ports comprises N−1self-feedback (y_(i,2)(n)˜y_(i,N)(n)) outputs and theoutput(y_(r,1)(n)˜y_(2,1)(n)) of the previous recurrent neural networkmodule, the bias input value is set as
 1. 7. The dynamic bandwidthallocation method of an Ethernet passive optical network as claimed inclaim 3, wherein the recurrent neural network modules are each disposedwith the same weighted array for adjusting a weight of an error of thePRNN predictor.
 8. The dynamic bandwidth allocation method of anEthernet passive optical network as claimed in claim 1, wherein the ERLSrule is based on a present and previous r−1 errors to update a weightw_(ij).
 9. The dynamic bandwidth allocation method of an Ethernetpassive optical network as claimed in claim 1, wherein the dynamicbandwidth allocation method comprising: 1) determining priorities ofclient traffic types and quality of service (QoS) parameters; and 2)determining a bandwidth for each client traffic type.
 10. The dynamicbandwidth allocation method of an Ethernet passive optical network asclaimed in claim 9, wherein the step of determining priorities of clienttraffic types comprises: 1) highest priority: a voice packet Q_(0,i); 2)second priority: a video packet L_(dp,i) facing a drop probability; 3)third priority: a video packet L_(d,i) facing a delay problem; 4) fourthpriority: a data packet L_(w,i) facing a delay problem; 5) fifthpriority: a common video packet Q_(1,i); and 6) lowest priority: acommon data packet Q_(2,i).
 11. The dynamic bandwidth allocation methodof an Ethernet passive optical network as claimed in claim 9, whereinthe step of determining quality of service (QoS) parameters comprises avideo packet delay threshold, a video packet drop probability thresholdand a data packet waiting time threshold.
 12. The dynamic bandwidthallocation method of an Ethernet passive optical network as claimed inclaim 9, wherein the step of determining a bandwidth for each clienttraffic type is implemented by the OLT distributing all availablebandwidth from the highest priority to the lowest priority until allavailable bandwidth is used.
 13. The dynamic bandwidth allocation methodof an Ethernet passive optical network as claimed in claim 9, whereinthe step of determining a bandwidth for each client traffic typecomprises: 1) Step 1: distributing a voice bandwidth G′_(0,i) to thefirst priority traffic type according to a packet value L_(0,i) storedin a queue by the ONU; 2) Step 2: distributing a video bandwidthG′_(1,i) to the second and third priority traffic types according to aremaining bandwidth from step 1 and packet values L_(dp,i) of the videopacket facing a drop probability and packet values L_(d,i) of the videopacket facing a delay problem; 3) Step 3: distributing a data bandwidthG′_(2,i) to the fourth priority traffic type according to a remainingbandwidth from step 2 and a packet value L_(w,i) of the data packetfacing a delay problem; 4) Step 4: distributing a common video bandwidthG″_(1,i) to the fifth priority traffic type according to a remainingbandwidth from step3 and a remaining packet value L_(1,i)-L_(d,i) of thecommon video packet queue Q_(1,i); 5) Step 5: distributing a databandwidth G″_(2,i) to the lowest priority traffic type according to aremaining bandwidth from step4 and a remaining packet valueL_(2,i)-L_(w,i) of the common data packet queue Q_(2,i); 6) Step 6:distributing remaining bandwidth, if there's still available bandwidthafter all required bandwidth is distributed to the ONUS, then theremaining bandwidth is again distributed to the voice bandwidth G″_(0,i)and video bandwidth G′″_(1,i) according to the ratio of packet valuesL_(0,i) and L_(1,i); and 7) Step 7: sending GRANT MPCPDU, wherein thedistributed bandwidth is the sum of the respective distributed value ofthe previous six steps.
 14. The dynamic bandwidth allocation method ofan Ethernet passive optical network as claimed in claim 13, whereindistributed bandwidth values G_(0,I), G_(1,I), and G_(2,i) are therespective sums of the outcomes of the six steps in claim
 14. 15. Thedynamic bandwidth allocation method of an Ethernet passive opticalnetwork as claimed in claim 14, wherein G_(0,i)=G′_(0,i)+G″_(2,i). 16.The dynamic bandwidth allocation method of an Ethernet passive opticalnetwork as claimed in claim 14, whereinG_(1,i)=G′_(1,i)+G″_(1,i)+G′″_(1,i).
 17. The dynamic bandwidthallocation method of an Ethernet passive optical network as claimed inclaim 14, wherein G_(2,i)=G′_(2,i)+G″_(2,i).